The Operating System of Experimental Science

The Problem

• -Most research infrastructure is invisible outside its home institution. Equipment, expertise, and capacity sit underutilized.
• -Industry teams with real R&D problems can't find the right academic partner without weeks of manual searching and warm introductions.
• -Researchers publish papers but have no structured way to signal what they can actually do next.

What Abstract Does

• -Maps research capabilities: publications, equipment, techniques, and the people behind them.
• -Routes problems to capabilities using AI-driven matching across researchers, labs, and facilities.
• -Lets users interact with research through natural language — ask questions, explore publications, generate collaboration ideas.
• -Makes scientific infrastructure discoverable and accessible beyond personal networks.

Why Now

• -Open metadata (OpenAlex, ORCID, institutional databases) finally makes it possible to map the research landscape programmatically.
• -Large language models can now read, summarize, and reason about scientific text at scale.
• -Universities and research facilities are under increasing pressure to demonstrate utilization and societal impact.
• -Industry R&D cycles are accelerating. The cost of not finding the right partner is measured in months and missed markets.

Vision

A world where any research problem can find the right capability — and any capability can find the problems worth solving. Abstract removes the friction between knowing and doing in science.